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Suicidality

Developed by sentinet
Text classification model based on ELECTRA architecture for detecting expressions of suicidal tendencies in text
Downloads 342
Release Time : 8/31/2023

Model Overview

This model is specifically designed to analyze text content and identify vocabulary sequences that may indicate suicidal tendencies, aiding in mental health risk assessment.

Model Features

High Accuracy Detection
The model achieves 93.9% accuracy on the validation set, reliably identifying texts with suicidal tendencies
Multi-source Data Training
Incorporates labeled data from various platforms such as Reddit and Twitter to ensure model generalization
Ethical Considerations
The model design fully considers the ethical implications of sensitive topics, emphasizing the need for manual review of prediction results

Model Capabilities

Suicidal tendency text classification
Sentiment analysis
Depression content recognition
Self-harm content detection

Use Cases

Mental Health Monitoring
Social Media Content Screening
Automatically scans user posts on social media platforms to identify potential suicide risks
Helps platforms promptly identify high-risk users and provide intervention
Psychological Counseling Assistance
Analyzes text content in consultation records to assist psychologists in assessing patient risk levels
Improves risk assessment efficiency and reduces manual screening workload
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